Thermodynamic Approach for the Identification of Instability in the Wood Using Acoustic Emission Technology

Abstract

In order to monitor the crack growth of the wood material better and reduce failure risks, this paper studied the attenuation characteristics of acoustic emission signals in wood through pencil lead breaking (PLB) tests, in the aim of estimating the true amplitude value of the acoustic emission source signal. The tensile test of the double cantilever beam (DCB) specimens was used to simulate the crack tip growth within wood material, monitoring acoustic activity and location of crack tips within wood material using acoustic emission technology and digital image correlation (DIC). Results showed that the attenuation degree of acoustic emission signals increased exponentially as the propagation distance increased, and the relationship between relative amplitude attenuation rate and the propagation distance of the acoustic emission signal was established by the regression method, which provides the input parameters for the establishment of the crack instability prediction model in the next step. Based on a thermodynamic approach, a theoretical model for predicting crack instability was established, and the model was verified by DCB tests. The model uses acoustic emission parameters as the basis for judging whether the crack is instable. It provides theoretical support for the application of acoustic emission technology in wood health monitoring.

Influencing Factors in Acoustic Emission Detection: A Literature Review Focusing on Grain Angle and High/Low Tree Ring Density of Scots Pine

“…The investigation showed that the most monitored acoustic Eeission parameters were amplitude (A), energy (E) and counts (C), which were frequently studied against time, crack length and load (even in their cumulative form) with their distribution often highlighted. Among the parameters less frequently studied there are the frequency characteristics [11,[16][17][18][19][20][21], other parameters such as the energy release rate (G) [22], the fracture toughness (K) [23,24], root mean square of the signal voltage (RMS) [25][26][27], density surface energy value (DSV) [16,23], stress (σ), strain (ε) [20,[28][29][30][31][32] and modulus of elasticity (MoE) [32,33].…”

“…In Shao et al [39] a theoretical approach was presented in the study of the fractal theory applied to examine the fracture surfaces of five types of woods. In Zhao et al [22], based on thermodynamic approach, a theoretical model for predicting crack instability was established and the model was verified by double cantilever beam (DCB) tests.…”

Differential Energy Criterion of Brittle Fracture as a Criterion for Wood’s Transition to the Plastic Deformation Stage

“…In this area, a generalized criterion for the maximum energy release rate is known [9]. Energy release in the process of damage and destruction of wood [10] and rocks [11] can be estimated indirectly by recording acoustic emissions.…”

“…Load-displacement curves for uniaxial compression of wood [4,26,27] and materials such as sandstone and concrete [18,28] have certain similarities. The similarity of loaddisplacement curves for various indicates that some methods of analyzing rock behavior under load can be adapted to analyze wood failure, subject to certain limitations associated with different material properties [4,22,29]; for example, the acoustic emission analysis mentioned above is an effective support tool for experimental studies of both rock and wood failure [10,11,[29][30][31]. The generalization of experimental data has formed the basis of a number of defining models of the mechanical behavior of wood.…”

Error Analysis of Limestone Acoustic Emission B-Value under Uniaxial Compression

“…The b-value was originally proposed and used in seismological studies by Gutenberg et al [9] . The b-value is also widely used in the study of rocks because of the similarity between the energy signal released when a rock breaks and the energy signal released by an earthquake [10][11][12][13] . The b-value is often calculated using the maximum likelihood and least square method.…”